Newer
Older
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
#!/usr/bin/python
# programmer : bbc
# usage:
import sys
import argparse as ap
import logging
import subprocess
import pandas as pd
from multiprocessing import Pool
logging.basicConfig(level=10)
def prepare_argparser():
description = "Make wig file for given bed using bam"
epilog = "For command line options of each command, type %(prog)% COMMAND -h"
argparser = ap.ArgumentParser(description=description, epilog = epilog)
argparser.add_argument("-i","--input",dest = "infile",type=str,required=True, help="input BAM file")
argparser.add_argument("-g","--genome",dest = "genome",type=str,required=True, help="genome", default="hg19")
#argparser.add_argument("-b","--bed",dest="bedfile",type=str,required=True, help = "Gene locus in bed format")
#argparser.add_argument("-s","--strandtype",dest="stranded",type=str,default="none", choices=["none","reverse","yes"])
#argparser.add_argument("-n","--name",dest="trackName",type=str,default="UserTrack",help = "track name for bedgraph header")
return(argparser)
def run_qc(files, controls, labels):
mbs_command = "multiBamSummary bins --bamfiles "+' '.join(files)+" -out sample_mbs.npz"
p = subprocess.Popen(mbs_command, shell=True)
#logging.debug(mbs_command)
p.communicate()
pcor_command = "plotCorrelation -in sample_mbs.npz --corMethod spearman --skipZeros --plotTitle \"Spearman Correlation of Read Counts\" --whatToPlot heatmap --colorMap RdYlBu --plotNumbers -o experiment.deeptools.heatmap_spearmanCorr_readCounts_v2.png --labels "+" ".join(labels)
#logging.debug(pcor_command)
p = subprocess.Popen(pcor_command, shell=True)
p.communicate()
#plotCoverage
pcov_command = "plotCoverage -b "+" ".join(files)+" --plotFile experiment.deeptools_coverage.png -n 1000000 --plotTitle \"sample coverage\" --ignoreDuplicates --minMappingQuality 10"
p = subprocess.Popen(pcov_command, shell=True)
p.communicate()
#draw fingerprints plots
for treat,ctrl,name in zip(files,controls,labels):
fp_command = "plotFingerprint -b "+treat+" "+ctrl+" --labels "+name+" control --plotFile "+name+".deeptools_fingerprints.png"
p = subprocess.Popen(fp_command, shell=True)
p.communicate()
def bam2bw_wrapper(command):
p = subprocess.Popen(command, shell=True)
p.communicate()
def run_signal(files, labels, genome):
#compute matrix and draw profile and heatmap
gene_bed = genome+"/gene.bed"#"/project/BICF/BICF_Core/bchen4/chipseq_analysis/test/genome/"+genome+"/gene.bed"
bw_commands = []
for f in files:
bw_commands.append("bamCoverage -bs 10 -b "+f+" -o "+f.replace("bam","bw"))
work_pool = Pool(min(len(files), 12))
work_pool.map(bam2bw_wrapper, bw_commands)
work_pool.close()
work_pool.join()
cm_command = "computeMatrix scale-regions -R "+gene_bed+" -a 3000 -b 3000 --regionBodyLength 5000 --skipZeros -S *.bw -o samples.deeptools_generegionscalematrix.gz"
p = subprocess.Popen(cm_command, shell=True)
p.communicate()
hm_command = "plotHeatmap -m samples.deeptools_generegionscalematrix.gz -out samples.deeptools_readsHeatmap.png"
p = subprocess.Popen(hm_command, shell=True)
p.communicate()
def run(dfile,genome):
#parse dfile, suppose data files are the same folder as design file
dfile = pd.read_csv(dfile)
#QC: multiBamSummary and plotCorrelation
run_qc(dfile['bamReads'], dfile['bamControl'], dfile['SampleID'])
#signal plots
run_signal(dfile['bamReads'],dfile['SampleID'],genome)
def main():
argparser = prepare_argparser()
args = argparser.parse_args()
run(args.infile, args.genome)
if __name__=="__main__":
main()